This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Abstract. To make accurate recommendations, recommendation systems currently require more data about a customer than is usually available. We conjecture that the weaknesses are due...
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...